Instructions to use rl-research/DR-Tulu-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rl-research/DR-Tulu-8B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="rl-research/DR-Tulu-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rl-research/DR-Tulu-8B")
model = AutoModelForCausalLM.from_pretrained("rl-research/DR-Tulu-8B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use rl-research/DR-Tulu-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "rl-research/DR-Tulu-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rl-research/DR-Tulu-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/rl-research/DR-Tulu-8B

SGLang

How to use rl-research/DR-Tulu-8B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "rl-research/DR-Tulu-8B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rl-research/DR-Tulu-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "rl-research/DR-Tulu-8B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rl-research/DR-Tulu-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use rl-research/DR-Tulu-8B with Docker Model Runner:
```
docker model run hf.co/rl-research/DR-Tulu-8B
```

Improve model card: Add pipeline tag, library name, project/code links, and sample usage

by nielsr HF Staff - opened Nov 26, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+54

-17

nielsr

Nov 26, 2025

This PR enhances the model card for DR Tulu-8B by:

Adding pipeline_tag: text-generation to improve discoverability on the Hugging Face Hub, as it's a deep research agent model.
Adding library_name: transformers as the model's configuration (config.json) indicates compatibility with Qwen3ForCausalLM, enabling the automated "how to use" widget.
Updating all paper links to point to the official Hugging Face paper page: DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research.
Adding prominent links to the Project Page (https://dr-tulu.github.io/) and Code (https://github.com/rlresearch/dr-tulu) for easier access.
Including a "Quick Start: Playing with DR Tulu Interactively" section with a code snippet directly from the GitHub README, providing practical usage instructions for the model within its dedicated dr-agent-lib framework.
Updating the BibTeX citation to the more complete @misc format found in the GitHub README.

These changes aim to make the model card more informative and user-friendly.

Improve model card: Add pipeline tag, library name, project/code links, and sample usage9c92bf75

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